Comparer des méthodes

	Analyse de survie prospective	Cox proportional hazards
Domaine	Épidémiologie	Épidémiologie
Famille	Process / pipeline	Process / pipeline
Année d'origine	1958–1972 (foundational methods); prospective design emphasis formalized by 1980s	1972
Auteur d'origine	Kaplan & Meier (estimator, 1958); Cox (proportional hazards model, 1972); prospective design formalised in modern clinical epidemiology	Sir David Roxbee Cox
Type	Longitudinal observational or experimental study design with time-to-event analysis	Semi-parametric regression model
Source fondatrice	Kleinbaum, D. G., & Klein, M. (2012). Survival Analysis: A Self-Learning Text (3rd ed.). Springer. ISBN: 978-1441966452	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
Alias	prospective time-to-event analysis, prospective failure-time analysis, forward-looking survival study, prospective event-time study	Cox regression, Cox PH model, proportional hazards model, CPH
Apparentées	5	5
Résumé	Prospective survival analysis is a longitudinal study design in which participants are enrolled before the event of interest occurs, followed forward in time under standardised conditions, and analysed using survival-analytic methods to estimate the time until a defined clinical endpoint — such as death, disease recurrence, or treatment failure. Because data are collected prospectively, exposure and covariate information are recorded before outcomes are known, substantially reducing recall and selection bias relative to retrospective approaches.	The Cox proportional hazards model is a semi-parametric regression method that estimates the effect of one or more covariates on the hazard — the instantaneous rate of an event such as death, relapse, or failure — while making no assumption about the shape of the baseline hazard function. Introduced by David Cox in 1972, it is the dominant tool for multivariable survival analysis in clinical and epidemiological research.